Solid-state image sensors are used in, for example, video cameras, and are presently realized in a number of forms including charge coupled devices (CCDs) and CMOS image sensors. These image sensors are based on a two dimensional array of pixels. Each pixel includes a sensing element that is capable of converting a portion of an optical image into an electronic signal. These electronic signals are then used to regenerate the optical image on, for example, a liquid crystal display (LCD).
More recently, however, CMOS image sensors have gained in popularity. Pure CMOS image sensors have benefited from advances in CMOS technology for microprocessors and ASICs and provide several advantages over CCD imagers. Shrinking lithography, coupled with advanced signal-processing algorithms, sets the stage for sensor array, array control, and image processing on one chip produced using these well-established CMOS techniques. Shrinking lithography should also decrease image-array cost due to smaller pixels. However, pixels cannot shrink too much, or they have an insufficient light-sensitive area. Nonetheless, shrinking lithography provides reduced metal-line widths that connect transistors and buses in the array.
Many image sensors utilize an electronic global shutter (GS) in which an image is captured by all of the pixels simultaneously (i.e., the integration of photo-electrons in the photodiode starts and stops at the same time for all pixels), and then the captured image is read out of the pixels, typically using a rolling shutter (RS) operation. Conventional CMOS image sensors that support GS operations include a Memory Node (MN) in each pixel that stores the image information (captured charge) until it is read out. That is, the image information (captured charge) generated in the photodiode of each pixel is transferred to and temporarily stored in the MN of each pixel, and then the captured charges are systematically (e.g., row by row) read out of the MN of each pixel (e.g., one row of pixels at a time) during the RS operation.
One possible way to reduce readout noise in global shutter pixel is to have an additional floating diffusion (FD) for each pixel, and reading out the captured charge using a correlated double sampling (CDS) readout operation. The CDS readout operation is perform by first resetting the FD and reading the reset (typically referred to as a sample-and-hold reset (SHR) signal value), and then transferring the captured charge from the pixel's MN to the pixel's FD and reading the image bit value (typically referred to as a sample-and-hold image (SHS) signal value). The CDS readout approach cancels out the kt/c associated with reset operations, which is otherwise dominant in low light. This noise reduction approach sets more strict design demands on the MN. Since the MN needs to optimized in a way that all the stored charge is transferred to the FD. The result of incomplete charge transfer is low light non-linearity and image lag.
There is an ongoing trend\demand to increase sensor resolution or to decrease pixel size. Decreasing the size of a global shutter pixel capable of CDS is impossible without compromising the active fill factor of the pixel due to the additional floating diffusion in each pixel and the associated control lines (typically four lines per row of pixels) that are required to support both GS image capture and rolling shutter CDS readout operations.
What is needed is an image sensor that supports GS image capture, utilizes low noise CDS readout operations, and facilitates higher resolution than that of conventional approaches by eliminating the need for disposing a floating diffusion in each pixel, and by reducing the number of control signals per pixel to less than four.